Overview

Brought to you by YData

Dataset statistics

Number of variables	28
Number of observations	75
Missing cells	75
Missing cells (%)	3.6%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	27.3 KiB
Average record size in memory	373.0 B

Variable types

Numeric	15
Categorical	11
DateTime	1
Unsupported	1

Alerts

`Campaign_5` has constant value "0"	Constant
`Complaint_Flag` has constant value "0"	Constant
`Contact_Cost` has constant value "3"	Constant
`Total_Revenue` has constant value "11"	Constant
`Annual_Income` is highly overall correlated with `Catalog_Orders` and 8 other fields	High correlation
`Campaign_1` is highly overall correlated with `Spent_Gold`	High correlation
`Campaign_2` is highly overall correlated with `Web_Orders`	High correlation
`Campaign_4` is highly overall correlated with `Spent_Fish` and 3 other fields	High correlation
`Catalog_Orders` is highly overall correlated with `Annual_Income` and 9 other fields	High correlation
`Spent_Fish` is highly overall correlated with `Annual_Income` and 8 other fields	High correlation
`Spent_Fruits` is highly overall correlated with `Annual_Income` and 7 other fields	High correlation
`Spent_Gold` is highly overall correlated with `Annual_Income` and 7 other fields	High correlation
`Spent_Meat` is highly overall correlated with `Annual_Income` and 10 other fields	High correlation
`Spent_Sweets` is highly overall correlated with `Catalog_Orders` and 4 other fields	High correlation
`Spent_Wines` is highly overall correlated with `Annual_Income` and 7 other fields	High correlation
`Store_Orders` is highly overall correlated with `Annual_Income` and 8 other fields	High correlation
`Web_Orders` is highly overall correlated with `Annual_Income` and 6 other fields	High correlation
`Web_Visits` is highly overall correlated with `Annual_Income` and 5 other fields	High correlation
`Campaign_1` is highly imbalanced (59.8%)	Imbalance
`Campaign_2` is highly imbalanced (64.7%)	Imbalance
`Campaign_4` is highly imbalanced (64.7%)	Imbalance
`Campaign_3` has 75 (100.0%) missing values	Missing
`User_Key` has unique values	Unique
`Annual_Income` has unique values	Unique
`Campaign_3` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`Last_Visit` has 2 (2.7%) zeros	Zeros
`Spent_Wines` has 1 (1.3%) zeros	Zeros
`Spent_Fruits` has 17 (22.7%) zeros	Zeros
`Spent_Fish` has 13 (17.3%) zeros	Zeros
`Spent_Sweets` has 16 (21.3%) zeros	Zeros
`Spent_Gold` has 1 (1.3%) zeros	Zeros
`Web_Orders` has 1 (1.3%) zeros	Zeros
`Catalog_Orders` has 21 (28.0%) zeros	Zeros

Reproduction

Analysis started	2025-07-25 16:44:48.731719
Analysis finished	2025-07-25 16:45:22.992873
Duration	34.26 seconds
Software version	ydata-profiling vv4.16.1
Download configuration	config.json

User_Key
Real number (ℝ)

Unique

Distinct	75
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5624.4267

Minimum	550
Maximum	10906
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	732.0 B

Quantile statistics

Minimum	550
5-th percentile	789.8
Q1	3075
median	5331
Q3	8428
95-th percentile	10545.6
Maximum	10906
Range	10356
Interquartile range (IQR)	5353

Descriptive statistics

Standard deviation	3098.2189
Coefficient of variation (CV)	0.55085062
Kurtosis	-1.1208389
Mean	5624.4267
Median Absolute Deviation (MAD)	2719
Skewness	0.124121
Sum	421832
Variance	9598960.4
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
9370	1	1.3%
4682	1	1.3%
4530	1	1.3%
8212	1	1.3%
6409	1	1.3%
9058	1	1.3%
4299	1	1.3%
10413	1	1.3%
1890	1	1.3%
8414	1	1.3%
Other values (65)	65	86.7%

Value	Count	Frequency (%)
550	1	1.3%
574	1	1.3%
615	1	1.3%
675	1	1.3%
839	1	1.3%
1041	1	1.3%
1045	1	1.3%
1404	1	1.3%
1890	1	1.3%
2156	1	1.3%

Value	Count	Frequency (%)
10906	1	1.3%
10837	1	1.3%
10821	1	1.3%
10708	1	1.3%
10476	1	1.3%
10413	1	1.3%
10129	1	1.3%
10104	1	1.3%
9938	1	1.3%
9905	1	1.3%

Birth_Year
Real number (ℝ)

Distinct	34
Distinct (%)	45.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1966.1733

Minimum	1945
Maximum	1991
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	732.0 B

Quantile statistics

Minimum	1945
5-th percentile	1948.7
Q1	1956.5
median	1969
Q3	1974
95-th percentile	1984.3
Maximum	1991
Range	46
Interquartile range (IQR)	17.5

Descriptive statistics

Standard deviation	11.127484
Coefficient of variation (CV)	0.0056594624
Kurtosis	-0.81922252
Mean	1966.1733
Median Absolute Deviation (MAD)	9
Skewness	0.044075034
Sum	147463
Variance	123.8209
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=34)

Value	Count	Frequency (%)
1971	7	9.3%
1974	5	6.7%
1978	4	5.3%
1958	4	5.3%
1960	4	5.3%
1956	4	5.3%
1952	3	4.0%
1975	3	4.0%
1969	3	4.0%
1955	3	4.0%
Other values (24)	35	46.7%

Value	Count	Frequency (%)
1945	1	1.3%
1948	3	4.0%
1949	1	1.3%
1950	2	2.7%
1951	1	1.3%
1952	3	4.0%
1954	1	1.3%
1955	3	4.0%
1956	4	5.3%
1957	2	2.7%

Value	Count	Frequency (%)
1991	1	1.3%
1988	1	1.3%
1987	1	1.3%
1985	1	1.3%
1984	1	1.3%
1983	2	2.7%
1978	4	5.3%
1977	2	2.7%
1975	3	4.0%
1974	5	6.7%

Edu_Level
Categorical

Distinct	5
Distinct (%)	6.7%
Missing	0
Missing (%)	0.0%
Memory size	4.3 KiB

Graduation	36
PhD	14
Master	14
2n Cycle	9
Basic	2

Length

Max length	10
Median length	8
Mean length	7.5733333
Min length	3

Characters and Unicode

Total characters	568
Distinct characters	22
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	PhD
2nd row	Graduation
3rd row	Master
4th row	Master
5th row	Graduation

Common Values

Value	Count	Frequency (%)
Graduation	36	48.0%
PhD	14	18.7%
Master	14	18.7%
2n Cycle	9	12.0%
Basic	2	2.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
graduation	36	42.9%
phd	14	16.7%
master	14	16.7%
2n	9	10.7%
cycle	9	10.7%
basic	2	2.4%

Most occurring characters

Value	Count	Frequency (%)
a	88	15.5%
r	50	8.8%
t	50	8.8%
n	45	7.9%
i	38	6.7%
G	36	6.3%
u	36	6.3%
d	36	6.3%
o	36	6.3%
e	23	4.0%
Other values (12)	130	22.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	568	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	88	15.5%
r	50	8.8%
t	50	8.8%
n	45	7.9%
i	38	6.7%
G	36	6.3%
u	36	6.3%
d	36	6.3%
o	36	6.3%
e	23	4.0%
Other values (12)	130	22.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	568	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	88	15.5%
r	50	8.8%
t	50	8.8%
n	45	7.9%
i	38	6.7%
G	36	6.3%
u	36	6.3%
d	36	6.3%
o	36	6.3%
e	23	4.0%
Other values (12)	130	22.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	568	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	88	15.5%
r	50	8.8%
t	50	8.8%
n	45	7.9%
i	38	6.7%
G	36	6.3%
u	36	6.3%
d	36	6.3%
o	36	6.3%
e	23	4.0%
Other values (12)	130	22.9%

Family_Status
Categorical

Distinct	5
Distinct (%)	6.7%
Missing	0
Missing (%)	0.0%
Memory size	4.2 KiB

Married	31
Together	24
Single	9
Divorced	8
Widow	3

Length

Max length	8
Median length	7
Mean length	7.2266667
Min length	5

Characters and Unicode

Total characters	542
Distinct characters	19
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Married
2nd row	Married
3rd row	Widow
4th row	Married
5th row	Divorced

Common Values

Value	Count	Frequency (%)
Married	31	41.3%
Together	24	32.0%
Single	9	12.0%
Divorced	8	10.7%
Widow	3	4.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
married	31	41.3%
together	24	32.0%
single	9	12.0%
divorced	8	10.7%
widow	3	4.0%

Most occurring characters

Value	Count	Frequency (%)
e	96	17.7%
r	94	17.3%
i	51	9.4%
d	42	7.7%
o	35	6.5%
g	33	6.1%
M	31	5.7%
a	31	5.7%
T	24	4.4%
t	24	4.4%
Other values (9)	81	14.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	542	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	96	17.7%
r	94	17.3%
i	51	9.4%
d	42	7.7%
o	35	6.5%
g	33	6.1%
M	31	5.7%
a	31	5.7%
T	24	4.4%
t	24	4.4%
Other values (9)	81	14.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	542	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	96	17.7%
r	94	17.3%
i	51	9.4%
d	42	7.7%
o	35	6.5%
g	33	6.1%
M	31	5.7%
a	31	5.7%
T	24	4.4%
t	24	4.4%
Other values (9)	81	14.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	542	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	96	17.7%
r	94	17.3%
i	51	9.4%
d	42	7.7%
o	35	6.5%
g	33	6.1%
M	31	5.7%
a	31	5.7%
T	24	4.4%
t	24	4.4%
Other values (9)	81	14.9%

Annual_Income
Real number (ℝ)

High correlation Unique

Distinct	75
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	50133.84

Minimum	8820
Maximum	85738
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	732.0 B

Quantile statistics

Minimum	8820
5-th percentile	19988.1
Q1	33832
median	51876
Q3	64918.5
95-th percentile	80775
Maximum	85738
Range	76918
Interquartile range (IQR)	31086.5

Descriptive statistics

Standard deviation	19862.369
Coefficient of variation (CV)	0.39618687
Kurtosis	-1.0018271
Mean	50133.84
Median Absolute Deviation (MAD)	15801
Skewness	-0.035776589
Sum	3760038
Variance	3.9451371 × 10⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
65846	1	1.3%
51876	1	1.3%
78427	1	1.3%
39791	1	1.3%
57136	1	1.3%
79800	1	1.3%
70971	1	1.3%
72570	1	1.3%
42033	1	1.3%
33419	1	1.3%
Other values (65)	65	86.7%

Value	Count	Frequency (%)
8820	1	1.3%
14045	1	1.3%
16626	1	1.3%
19510	1	1.3%
20193	1	1.3%
22390	1	1.3%
22554	1	1.3%
23331	1	1.3%
23957	1	1.3%
24762	1	1.3%

Value	Count	Frequency (%)
85738	1	1.3%
83145	1	1.3%
82582	1	1.3%
82427	1	1.3%
80067	1	1.3%
79800	1	1.3%
78427	1	1.3%
77981	1	1.3%
76140	1	1.3%
75794	1	1.3%

Kids_Count
Categorical

Distinct	3
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	3.8 KiB

0	43
1	28
2	4

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	75
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	43	57.3%
1	28	37.3%
2	4	5.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	43	57.3%
1	28	37.3%
2	4	5.3%

Most occurring characters

Value	Count	Frequency (%)
0	43	57.3%
1	28	37.3%
2	4	5.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	43	57.3%
1	28	37.3%
2	4	5.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	43	57.3%
1	28	37.3%
2	4	5.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	43	57.3%
1	28	37.3%
2	4	5.3%

Teens_Count
Categorical

Distinct	3
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	3.8 KiB

1	37
0	36
2	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	75
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
1	37	49.3%
0	36	48.0%
2	2	2.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	37	49.3%
0	36	48.0%
2	2	2.7%

Most occurring characters

Value	Count	Frequency (%)
1	37	49.3%
0	36	48.0%
2	2	2.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
1	37	49.3%
0	36	48.0%
2	2	2.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
1	37	49.3%
0	36	48.0%
2	2	2.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
1	37	49.3%
0	36	48.0%
2	2	2.7%

Reg_Date
Date

Distinct	70
Distinct (%)	93.3%
Missing	0
Missing (%)	0.0%
Memory size	732.0 B

Minimum	2012-01-10 00:00:00
Maximum	2014-12-03 00:00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=50)

Last_Visit
Real number (ℝ)

Zeros

Distinct	51
Distinct (%)	68.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	50.373333

Minimum	0
Maximum	96
Zeros	2
Zeros (%)	2.7%
Negative	0
Negative (%)	0.0%
Memory size	732.0 B

Quantile statistics

Minimum	0
5-th percentile	3
Q1	27.5
median	51
Q3	76
95-th percentile	92
Maximum	96
Range	96
Interquartile range (IQR)	48.5

Descriptive statistics

Standard deviation	28.264089
Coefficient of variation (CV)	0.5610923
Kurtosis	-1.1236822
Mean	50.373333
Median Absolute Deviation (MAD)	25
Skewness	-0.092543893
Sum	3778
Variance	798.85874
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
50	3	4.0%
54	3	4.0%
18	3	4.0%
63	3	4.0%
16	2	2.7%
96	2	2.7%
38	2	2.7%
76	2	2.7%
67	2	2.7%
89	2	2.7%
Other values (41)	51	68.0%

Value	Count	Frequency (%)
0	2	2.7%
1	1	1.3%
3	2	2.7%
8	2	2.7%
14	1	1.3%
16	2	2.7%
17	1	1.3%
18	3	4.0%
19	1	1.3%
20	1	1.3%

Value	Count	Frequency (%)
96	2	2.7%
95	1	1.3%
92	2	2.7%
89	2	2.7%
88	1	1.3%
87	1	1.3%
86	2	2.7%
85	2	2.7%
83	1	1.3%
82	1	1.3%

Spent_Wines
Real number (ℝ)

High correlation Zeros

Distinct	66
Distinct (%)	88.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	247.48

Minimum	0
Maximum	1099
Zeros	1
Zeros (%)	1.3%
Negative	0
Negative (%)	0.0%
Memory size	732.0 B

Quantile statistics

Minimum	0
5-th percentile	5
Q1	27.5
median	135
Q3	367.5
95-th percentile	930.7
Maximum	1099
Range	1099
Interquartile range (IQR)	340

Descriptive statistics

Standard deviation	288.11852
Coefficient of variation (CV)	1.1642093
Kurtosis	1.2676314
Mean	247.48
Median Absolute Deviation (MAD)	125
Skewness	1.4103676
Sum	18561
Variance	83012.28
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
14	3	4.0%
8	3	4.0%
5	2	2.7%
587	2	2.7%
11	2	2.7%
46	2	2.7%
135	2	2.7%
562	1	1.3%
99	1	1.3%
1060	1	1.3%
Other values (56)	56	74.7%

Value	Count	Frequency (%)
0	1	1.3%
2	1	1.3%
4	1	1.3%
5	2	2.7%
6	1	1.3%
8	3	4.0%
9	1	1.3%
10	1	1.3%
11	2	2.7%
12	1	1.3%

Value	Count	Frequency (%)
1099	1	1.3%
1060	1	1.3%
1001	1	1.3%
972	1	1.3%
913	1	1.3%
777	1	1.3%
754	1	1.3%
587	2	2.7%
586	1	1.3%
571	1	1.3%

Spent_Fruits
Real number (ℝ)

High correlation Zeros

Distinct	35
Distinct (%)	46.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	27.786667

Minimum	0
Maximum	160
Zeros	17
Zeros (%)	22.7%
Negative	0
Negative (%)	0.0%
Memory size	732.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	10
Q3	36
95-th percentile	125.4
Maximum	160
Range	160
Interquartile range (IQR)	35

Descriptive statistics

Standard deviation	41.084387
Coefficient of variation (CV)	1.4785648
Kurtosis	2.3812242
Mean	27.786667
Median Absolute Deviation (MAD)	10
Skewness	1.8175877
Sum	2084
Variance	1687.9268
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=35)

Value	Count	Frequency (%)
0	17	22.7%
1	6	8.0%
4	5	6.7%
17	4	5.3%
36	3	4.0%
15	3	4.0%
2	3	4.0%
10	3	4.0%
6	2	2.7%
3	2	2.7%
Other values (25)	27	36.0%

Value	Count	Frequency (%)
0	17	22.7%
1	6	8.0%
2	3	4.0%
3	2	2.7%
4	5	6.7%
6	2	2.7%
8	1	1.3%
10	3	4.0%
11	1	1.3%
12	1	1.3%

Value	Count	Frequency (%)
160	1	1.3%
147	1	1.3%
140	1	1.3%
131	1	1.3%
123	1	1.3%
120	2	2.7%
97	1	1.3%
83	1	1.3%
81	1	1.3%
66	2	2.7%

Spent_Meat
Real number (ℝ)

High correlation

Distinct	62
Distinct (%)	82.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	157.08

Minimum	2
Maximum	898
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	732.0 B

Quantile statistics

Minimum	2
5-th percentile	4.7
Q1	19.5
median	47
Q3	187.5
95-th percentile	633.4
Maximum	898
Range	896
Interquartile range (IQR)	168

Descriptive statistics

Standard deviation	225.14624
Coefficient of variation (CV)	1.4333222
Kurtosis	1.9450463
Mean	157.08
Median Absolute Deviation (MAD)	37
Skewness	1.7359243
Sum	11781
Variance	50690.831
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
11	3	4.0%
4	2	2.7%
30	2	2.7%
2	2	2.7%
10	2	2.7%
12	2	2.7%
44	2	2.7%
22	2	2.7%
5	2	2.7%
21	2	2.7%
Other values (52)	54	72.0%

Value	Count	Frequency (%)
2	2	2.7%
4	2	2.7%
5	2	2.7%
7	2	2.7%
8	1	1.3%
9	1	1.3%
10	2	2.7%
11	3	4.0%
12	2	2.7%
13	1	1.3%

Value	Count	Frequency (%)
898	1	1.3%
813	1	1.3%
731	1	1.3%
653	1	1.3%
625	1	1.3%
599	1	1.3%
595	1	1.3%
572	1	1.3%
550	1	1.3%
530	1	1.3%

Spent_Fish
Real number (ℝ)

High correlation Zeros

Distinct	41
Distinct (%)	54.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	29.253333

Minimum	0
Maximum	247
Zeros	13
Zeros (%)	17.3%
Negative	0
Negative (%)	0.0%
Memory size	732.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	3
median	16
Q3	33
95-th percentile	118.1
Maximum	247
Range	247
Interquartile range (IQR)	30

Descriptive statistics

Standard deviation	44.352426
Coefficient of variation (CV)	1.5161495
Kurtosis	9.4842697
Mean	29.253333
Median Absolute Deviation (MAD)	14
Skewness	2.8784742
Sum	2194
Variance	1967.1377
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=41)

Value	Count	Frequency (%)
0	13	17.3%
3	5	6.7%
15	4	5.3%
2	4	5.3%
6	3	4.0%
17	3	4.0%
21	3	4.0%
8	2	2.7%
20	2	2.7%
4	2	2.7%
Other values (31)	34	45.3%

Value	Count	Frequency (%)
0	13	17.3%
2	4	5.3%
3	5	6.7%
4	2	2.7%
6	3	4.0%
7	1	1.3%
8	2	2.7%
10	1	1.3%
12	1	1.3%
13	1	1.3%

Value	Count	Frequency (%)
247	1	1.3%
180	1	1.3%
156	1	1.3%
151	1	1.3%
104	1	1.3%
93	1	1.3%
85	1	1.3%
80	1	1.3%
76	1	1.3%
63	1	1.3%

Spent_Sweets
Real number (ℝ)

High correlation Zeros

Distinct	31
Distinct (%)	41.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	24.413333

Minimum	0
Maximum	173
Zeros	16
Zeros (%)	21.3%
Negative	0
Negative (%)	0.0%
Memory size	732.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	6
Q3	23
95-th percentile	125.3
Maximum	173
Range	173
Interquartile range (IQR)	22

Descriptive statistics

Standard deviation	40.967717
Coefficient of variation (CV)	1.6780878
Kurtosis	3.5794725
Mean	24.413333
Median Absolute Deviation (MAD)	6
Skewness	2.1264743
Sum	1831
Variance	1678.3539
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=31)

Value	Count	Frequency (%)
0	16	21.3%
1	8	10.7%
2	8	10.7%
13	6	8.0%
26	3	4.0%
4	3	4.0%
40	2	2.7%
11	2	2.7%
20	2	2.7%
19	2	2.7%
Other values (21)	23	30.7%

Value	Count	Frequency (%)
0	16	21.3%
1	8	10.7%
2	8	10.7%
3	2	2.7%
4	3	4.0%
6	1	1.3%
8	1	1.3%
10	2	2.7%
11	2	2.7%
12	1	1.3%

Value	Count	Frequency (%)
173	1	1.3%
141	1	1.3%
137	1	1.3%
126	1	1.3%
125	1	1.3%
123	1	1.3%
118	1	1.3%
107	1	1.3%
87	1	1.3%
57	1	1.3%

Spent_Gold
Real number (ℝ)

High correlation Zeros

Distinct	49
Distinct (%)	65.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	50.08

Minimum	0
Maximum	241
Zeros	1
Zeros (%)	1.3%
Negative	0
Negative (%)	0.0%
Memory size	732.0 B

Quantile statistics

Minimum	0
5-th percentile	2
Q1	9
median	26
Q3	63.5
95-th percentile	201.6
Maximum	241
Range	241
Interquartile range (IQR)	54.5

Descriptive statistics

Standard deviation	60.24853
Coefficient of variation (CV)	1.2030457
Kurtosis	2.4977666
Mean	50.08
Median Absolute Deviation (MAD)	19
Skewness	1.7703942
Sum	3756
Variance	3629.8854
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=49)

Value	Count	Frequency (%)
7	4	5.3%
2	4	5.3%
13	4	5.3%
26	3	4.0%
42	3	4.0%
224	2	2.7%
4	2	2.7%
18	2	2.7%
21	2	2.7%
9	2	2.7%
Other values (39)	47	62.7%

Value	Count	Frequency (%)
0	1	1.3%
1	2	2.7%
2	4	5.3%
3	2	2.7%
4	2	2.7%
5	2	2.7%
6	1	1.3%
7	4	5.3%
9	2	2.7%
11	1	1.3%

Value	Count	Frequency (%)
241	1	1.3%
227	1	1.3%
224	2	2.7%
192	1	1.3%
159	1	1.3%
141	1	1.3%
138	1	1.3%
135	1	1.3%
127	1	1.3%
114	1	1.3%

Promo_Purchases
Real number (ℝ)

Distinct	9
Distinct (%)	12.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.4933333

Minimum	1
Maximum	12
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	732.0 B

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	3
95-th percentile	6
Maximum	12
Range	11
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	2.1205133
Coefficient of variation (CV)	0.85047324
Kurtosis	7.3763463
Mean	2.4933333
Median Absolute Deviation (MAD)	1
Skewness	2.381454
Sum	187
Variance	4.4965766
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
1	33	44.0%
2	16	21.3%
4	9	12.0%
3	8	10.7%
5	4	5.3%
6	2	2.7%
7	1	1.3%
11	1	1.3%
12	1	1.3%

Value	Count	Frequency (%)
1	33	44.0%
2	16	21.3%
3	8	10.7%
4	9	12.0%
5	4	5.3%
6	2	2.7%
7	1	1.3%
11	1	1.3%
12	1	1.3%

Value	Count	Frequency (%)
12	1	1.3%
11	1	1.3%
7	1	1.3%
6	2	2.7%
5	4	5.3%
4	9	12.0%
3	8	10.7%
2	16	21.3%
1	33	44.0%

Web_Orders
Real number (ℝ)

High correlation Zeros

Distinct	11
Distinct (%)	14.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.7466667

Minimum	0
Maximum	11
Zeros	1
Zeros (%)	1.3%
Negative	0
Negative (%)	0.0%
Memory size	732.0 B

Quantile statistics

Minimum	0
5-th percentile	1
Q1	2
median	3
Q3	5
95-th percentile	8
Maximum	11
Range	11
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	2.3715278
Coefficient of variation (CV)	0.63297006
Kurtosis	0.95628221
Mean	3.7466667
Median Absolute Deviation (MAD)	1
Skewness	1.0289826
Sum	281
Variance	5.6241441
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
3	20	26.7%
1	12	16.0%
2	10	13.3%
4	10	13.3%
5	7	9.3%
7	7	9.3%
6	3	4.0%
11	2	2.7%
8	2	2.7%
0	1	1.3%

Value	Count	Frequency (%)
0	1	1.3%
1	12	16.0%
2	10	13.3%
3	20	26.7%
4	10	13.3%
5	7	9.3%
6	3	4.0%
7	7	9.3%
8	2	2.7%
9	1	1.3%

Value	Count	Frequency (%)
11	2	2.7%
9	1	1.3%
8	2	2.7%
7	7	9.3%
6	3	4.0%
5	7	9.3%
4	10	13.3%
3	20	26.7%
2	10	13.3%
1	12	16.0%

Catalog_Orders
Real number (ℝ)

High correlation Zeros

Distinct	10
Distinct (%)	13.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.6

Minimum	0
Maximum	11
Zeros	21
Zeros (%)	28.0%
Negative	0
Negative (%)	0.0%
Memory size	732.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	4
95-th percentile	9
Maximum	11
Range	11
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.8945429
Coefficient of variation (CV)	1.1132857
Kurtosis	0.86163329
Mean	2.6
Median Absolute Deviation (MAD)	1
Skewness	1.2564976
Sum	195
Variance	8.3783784
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	21	28.0%
1	17	22.7%
2	9	12.0%
3	6	8.0%
6	6	8.0%
5	5	6.7%
9	4	5.3%
4	4	5.3%
11	2	2.7%
7	1	1.3%

Value	Count	Frequency (%)
0	21	28.0%
1	17	22.7%
2	9	12.0%
3	6	8.0%
4	4	5.3%
5	5	6.7%
6	6	8.0%
7	1	1.3%
9	4	5.3%
11	2	2.7%

Value	Count	Frequency (%)
11	2	2.7%
9	4	5.3%
7	1	1.3%
6	6	8.0%
5	5	6.7%
4	4	5.3%
3	6	8.0%
2	9	12.0%
1	17	22.7%
0	21	28.0%

Store_Orders
Real number (ℝ)

High correlation

Distinct	12
Distinct (%)	16.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.4933333

Minimum	2
Maximum	13
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	732.0 B

Quantile statistics

Minimum	2
5-th percentile	2
Q1	3
median	4
Q3	7
95-th percentile	12
Maximum	13
Range	11
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.9745467
Coefficient of variation (CV)	0.54148301
Kurtosis	0.32389756
Mean	5.4933333
Median Absolute Deviation (MAD)	1
Skewness	1.1114826
Sum	412
Variance	8.8479279
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
4	18	24.0%
3	15	20.0%
6	8	10.7%
7	7	9.3%
5	7	9.3%
2	6	8.0%
12	4	5.3%
10	3	4.0%
8	2	2.7%
11	2	2.7%
Other values (2)	3	4.0%

Value	Count	Frequency (%)
2	6	8.0%
3	15	20.0%
4	18	24.0%
5	7	9.3%
6	8	10.7%
7	7	9.3%
8	2	2.7%
9	1	1.3%
10	3	4.0%
11	2	2.7%

Value	Count	Frequency (%)
13	2	2.7%
12	4	5.3%
11	2	2.7%
10	3	4.0%
9	1	1.3%
8	2	2.7%
7	7	9.3%
6	8	10.7%
5	7	9.3%
4	18	24.0%

Web_Visits
Real number (ℝ)

High correlation

Distinct	9
Distinct (%)	12.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.2

Minimum	1
Maximum	9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	732.0 B

Quantile statistics

Minimum	1
5-th percentile	1
Q1	3
median	6
Q3	7
95-th percentile	8
Maximum	9
Range	8
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.3480872
Coefficient of variation (CV)	0.45155523
Kurtosis	-1.0183998
Mean	5.2
Median Absolute Deviation (MAD)	1
Skewness	-0.38864421
Sum	390
Variance	5.5135135
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
7	16	21.3%
5	11	14.7%
6	11	14.7%
2	10	13.3%
8	9	12.0%
1	6	8.0%
4	5	6.7%
3	4	5.3%
9	3	4.0%

Value	Count	Frequency (%)
1	6	8.0%
2	10	13.3%
3	4	5.3%
4	5	6.7%
5	11	14.7%
6	11	14.7%
7	16	21.3%
8	9	12.0%
9	3	4.0%

Value	Count	Frequency (%)
9	3	4.0%
8	9	12.0%
7	16	21.3%
6	11	14.7%
5	11	14.7%
4	5	6.7%
3	4	5.3%
2	10	13.3%
1	6	8.0%

Campaign_1
Categorical

High correlation Imbalance

Distinct	2
Distinct (%)	2.7%
Missing	0
Missing (%)	0.0%
Memory size	3.8 KiB

0	69
1	6

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	75
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	69	92.0%
1	6	8.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	69	92.0%
1	6	8.0%

Most occurring characters

Value	Count	Frequency (%)
0	69	92.0%
1	6	8.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	69	92.0%
1	6	8.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	69	92.0%
1	6	8.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	69	92.0%
1	6	8.0%

Campaign_2
Categorical

High correlation Imbalance

Distinct	2
Distinct (%)	2.7%
Missing	0
Missing (%)	0.0%
Memory size	3.8 KiB

0	70
1	5

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	75
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	70	93.3%
1	5	6.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	70	93.3%
1	5	6.7%

Most occurring characters

Value	Count	Frequency (%)
0	70	93.3%
1	5	6.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	70	93.3%
1	5	6.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	70	93.3%
1	5	6.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	70	93.3%
1	5	6.7%

Campaign_3
Unsupported

Missing Rejected Unsupported

Missing	75
Missing (%)	100.0%
Memory size	732.0 B

Campaign_4
Categorical

High correlation Imbalance

Distinct	2
Distinct (%)	2.7%
Missing	0
Missing (%)	0.0%
Memory size	3.8 KiB

0	70
1	5

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	75
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	70	93.3%
1	5	6.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	70	93.3%
1	5	6.7%

Most occurring characters

Value	Count	Frequency (%)
0	70	93.3%
1	5	6.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	70	93.3%
1	5	6.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	70	93.3%
1	5	6.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	70	93.3%
1	5	6.7%

Campaign_5
Categorical

Constant

Distinct	1
Distinct (%)	1.3%
Missing	0
Missing (%)	0.0%
Memory size	3.8 KiB

0	75

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	75
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	75	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	75	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	75	100.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	75	100.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	75	100.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	75	100.0%

Complaint_Flag
Categorical

Constant

Distinct	1
Distinct (%)	1.3%
Missing	0
Missing (%)	0.0%
Memory size	3.8 KiB

0	75

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	75
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	75	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	75	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	75	100.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	75	100.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	75	100.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	75	100.0%

Contact_Cost
Categorical

Constant

Distinct	1
Distinct (%)	1.3%
Missing	0
Missing (%)	0.0%
Memory size	3.8 KiB

3	75

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	75
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3
2nd row	3
3rd row	3
4th row	3
5th row	3

Common Values

Value	Count	Frequency (%)
3	75	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
3	75	100.0%

Most occurring characters

Value	Count	Frequency (%)
3	75	100.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
3	75	100.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
3	75	100.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	75	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
3	75	100.0%

Total_Revenue
Categorical

Constant

Distinct	1
Distinct (%)	1.3%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

11	75

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	150
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	11
2nd row	11
3rd row	11
4th row	11
5th row	11

Common Values

Value	Count	Frequency (%)
11	75	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
11	75	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	150	100.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	150	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
1	150	100.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	150	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
1	150	100.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	150	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
1	150	100.0%

Interactions

Correlations

	Annual_Income	Birth_Year	Campaign_1	Campaign_2	Campaign_4	Catalog_Orders	Edu_Level	Family_Status	Kids_Count	Last_Visit	Promo_Purchases	Spent_Fish	Spent_Fruits	Spent_Gold	Spent_Meat	Spent_Sweets	Spent_Wines	Store_Orders	Teens_Count	User_Key	Web_Orders	Web_Visits
Annual_Income	1.000	-0.215	0.000	0.137	0.364	0.819	0.000	0.213	0.343	-0.075	-0.114	0.565	0.617	0.576	0.808	0.448	0.858	0.752	0.370	0.145	0.554	-0.635
Birth_Year	-0.215	1.000	0.000	0.000	0.096	-0.307	0.190	0.000	0.000	-0.072	-0.202	-0.136	-0.074	-0.141	-0.212	-0.034	-0.276	-0.127	0.284	-0.019	-0.127	0.236
Campaign_1	0.000	0.000	1.000	0.000	0.184	0.296	0.000	0.191	0.000	0.000	0.000	0.000	0.000	0.555	0.000	0.000	0.000	0.000	0.205	0.000	0.000	0.000
Campaign_2	0.137	0.000	0.000	1.000	0.000	0.000	0.054	0.000	0.000	0.199	0.287	0.000	0.000	0.000	0.000	0.000	0.496	0.370	0.013	0.000	0.560	0.302
Campaign_4	0.364	0.096	0.184	0.000	1.000	0.497	0.000	0.466	0.163	0.000	0.000	0.627	0.278	0.328	0.555	0.000	0.548	0.261	0.051	0.000	0.000	0.606
Catalog_Orders	0.819	-0.307	0.296	0.000	0.497	1.000	0.000	0.269	0.244	-0.092	0.006	0.675	0.666	0.720	0.862	0.516	0.863	0.680	0.148	0.095	0.629	-0.537
Edu_Level	0.000	0.190	0.000	0.054	0.000	0.000	1.000	0.000	0.000	0.000	0.000	0.031	0.086	0.100	0.000	0.000	0.000	0.178	0.154	0.192	0.000	0.231
Family_Status	0.213	0.000	0.191	0.000	0.466	0.269	0.000	1.000	0.000	0.000	0.000	0.231	0.219	0.000	0.191	0.000	0.000	0.105	0.000	0.150	0.000	0.286
Kids_Count	0.343	0.000	0.000	0.000	0.163	0.244	0.000	0.000	1.000	0.121	0.133	0.198	0.165	0.000	0.000	0.053	0.270	0.266	0.000	0.000	0.235	0.494
Last_Visit	-0.075	-0.072	0.000	0.199	0.000	-0.092	0.000	0.000	0.121	1.000	0.062	-0.041	0.119	-0.015	-0.072	0.060	-0.126	-0.089	0.000	-0.066	-0.060	-0.054
Promo_Purchases	-0.114	-0.202	0.000	0.287	0.000	0.006	0.000	0.000	0.133	0.062	1.000	-0.168	-0.269	0.051	-0.044	-0.078	0.137	0.078	0.184	-0.051	0.307	0.416
Spent_Fish	0.565	-0.136	0.000	0.000	0.627	0.675	0.031	0.231	0.198	-0.041	-0.168	1.000	0.775	0.607	0.806	0.568	0.526	0.522	0.000	-0.046	0.483	-0.477
Spent_Fruits	0.617	-0.074	0.000	0.000	0.278	0.666	0.086	0.219	0.165	0.119	-0.269	0.775	1.000	0.629	0.740	0.634	0.475	0.561	0.000	-0.071	0.453	-0.544
Spent_Gold	0.576	-0.141	0.555	0.000	0.328	0.720	0.100	0.000	0.000	-0.015	0.051	0.607	0.629	1.000	0.671	0.437	0.604	0.437	0.000	0.081	0.610	-0.273
Spent_Meat	0.808	-0.212	0.000	0.000	0.555	0.862	0.000	0.191	0.000	-0.072	-0.044	0.806	0.740	0.671	1.000	0.547	0.816	0.750	0.000	-0.020	0.680	-0.502
Spent_Sweets	0.448	-0.034	0.000	0.000	0.000	0.516	0.000	0.000	0.053	0.060	-0.078	0.568	0.634	0.437	0.547	1.000	0.356	0.514	0.000	0.031	0.350	-0.428
Spent_Wines	0.858	-0.276	0.000	0.496	0.548	0.863	0.000	0.000	0.270	-0.126	0.137	0.526	0.475	0.604	0.816	0.356	1.000	0.802	0.000	0.082	0.722	-0.419
Store_Orders	0.752	-0.127	0.000	0.370	0.261	0.680	0.178	0.105	0.266	-0.089	0.078	0.522	0.561	0.437	0.750	0.514	0.802	1.000	0.000	-0.012	0.519	-0.563
Teens_Count	0.370	0.284	0.205	0.013	0.051	0.148	0.154	0.000	0.000	0.000	0.184	0.000	0.000	0.000	0.000	0.000	0.000	0.000	1.000	0.221	0.000	0.000
User_Key	0.145	-0.019	0.000	0.000	0.000	0.095	0.192	0.150	0.000	-0.066	-0.051	-0.046	-0.071	0.081	-0.020	0.031	0.082	-0.012	0.221	1.000	0.031	-0.085
Web_Orders	0.554	-0.127	0.000	0.560	0.000	0.629	0.000	0.000	0.235	-0.060	0.307	0.483	0.453	0.610	0.680	0.350	0.722	0.519	0.000	0.031	1.000	0.042
Web_Visits	-0.635	0.236	0.000	0.302	0.606	-0.537	0.231	0.286	0.494	-0.054	0.416	-0.477	-0.544	-0.273	-0.502	-0.428	-0.419	-0.563	0.000	-0.085	0.042	1.000

Missing values

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

	User_Key	Birth_Year	Edu_Level	Family_Status	Annual_Income	Kids_Count	Teens_Count	Reg_Date	Last_Visit	Spent_Wines	Spent_Fruits	Spent_Meat	Spent_Fish	Spent_Sweets	Spent_Gold	Promo_Purchases	Web_Orders	Catalog_Orders	Store_Orders	Web_Visits	Campaign_1	Campaign_3	Campaign_4	Contact_Cost	Total_Revenue
0	9370	1945	PhD	Married	65846	0	0	17-05-2013	68	562	81	276	80	40	81	1	6	3	6	4	0	NaN	0	3	11
1	4682	1958	Graduation	Married	51876	0	0	15-10-2013	88	99	27	102	28	48	6	1	2	2	8	1	0	NaN	0	3	11
2	4530	1948	Master	Widow	78427	0	0	24-10-2012	36	972	19	595	180	26	138	3	3	7	10	3	0	NaN	1	3	11
3	8212	1971	Master	Married	39791	0	1	28-03-2013	89	85	15	27	13	13	21	2	3	1	4	7	0	NaN	0	3	11
4	6409	1967	Graduation	Divorced	57136	0	0	18-05-2013	18	267	140	599	34	12	127	1	7	5	7	6	0	NaN	0	3	11
5	9058	1955	Graduation	Widow	79800	0	0	23-09-2012	65	1060	21	530	32	0	224	1	5	11	5	3	1	NaN	1	3	11
6	4299	1960	Graduation	Together	70971	0	1	21-09-2012	28	1001	17	572	93	125	17	7	11	11	5	7	0	NaN	0	3	11
7	10413	1984	Graduation	Married	72570	0	0	25-04-2014	67	274	83	216	151	141	224	1	4	6	12	1	0	NaN	0	3	11
8	1890	1971	2n Cycle	Together	42033	1	1	19-09-2012	95	11	1	4	2	0	7	1	1	0	2	7	0	NaN	0	3	11
9	8414	1962	PhD	Single	33419	0	1	17-08-2013	76	56	0	12	0	0	18	2	2	0	4	7	0	NaN	0	3	11

	User_Key	Birth_Year	Edu_Level	Family_Status	Annual_Income	Kids_Count	Teens_Count	Reg_Date	Last_Visit	Spent_Wines	Spent_Fruits	Spent_Meat	Spent_Fish	Spent_Sweets	Spent_Gold	Promo_Purchases	Web_Orders	Catalog_Orders	Store_Orders	Web_Visits	Campaign_1	Campaign_2	Campaign_3	Campaign_4	Contact_Cost	Total_Revenue
65	10129	1966	Graduation	Together	82427	0	0	12/3/2014	35	482	147	509	104	107	107	1	3	5	12	1	0	0	NaN	0	3	11
66	550	1952	Graduation	Divorced	62335	0	1	23-05-2013	87	243	131	217	85	6	26	2	3	3	13	2	0	0	NaN	0	3	11
67	1045	1965	Graduation	Together	52117	0	1	16-08-2012	55	112	10	107	30	0	20	2	5	2	4	7	0	0	NaN	0	3	11
68	4377	1971	Graduation	Married	52914	0	1	7/1/2013	32	254	10	44	30	10	227	2	7	3	3	7	1	0	NaN	0	3	11
69	5031	1974	Graduation	Together	83145	0	0	22-09-2012	14	777	35	731	39	137	114	1	5	9	11	2	0	0	NaN	0	3	11
70	1404	1968	Graduation	Together	34916	2	0	15-05-2013	89	51	23	82	33	0	42	4	5	1	3	9	0	0	NaN	0	3	11
71	5883	1972	Graduation	Married	77981	1	0	26-05-2013	78	138	120	204	16	126	60	3	7	4	7	5	0	0	NaN	0	3	11
72	5794	1974	PhD	Married	46374	0	1	17-03-2014	1	408	0	21	0	0	17	3	7	1	7	8	0	1	NaN	1	3	11
73	2612	1987	Graduation	Married	75794	0	0	24-12-2013	33	754	160	625	63	32	48	1	7	5	12	3	0	0	NaN	1	3	11
74	4149	1948	PhD	Together	76140	0	0	13-05-2014	57	586	66	653	17	0	26	1	5	9	6	2	0	0	NaN	0	3	11

Overview

Variables

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)